Steven D'Aprano writes:
> So, I'm, still trying to wrap my brain around async processing, and I
> started reading this tutorial:
>
> http://stackabuse.com/python-async-await-tutorial/
>
> and the very first paragraph broke my brain.
>
> "Asynchronous
On 4/4/2018 3:27 AM, Steven D'Aprano wrote:
So, I'm, still trying to wrap my brain around async processing, and I
started reading this tutorial:
http://stackabuse.com/python-async-await-tutorial/
and the very first paragraph broke my brain.
"Asynchronous programming has been gaining a lot of
On Thu, Apr 5, 2018 at 1:48 AM, Julien Salort wrote:
> Le 04/04/2018 à 14:45, Chris Angelico a écrit :
>> How do you use run_in_executor to turn this asynchronous, and how
>> would this compare to creating one thread for each camera?
>
> This is exactely like creating a thread.
Le 04/04/2018 à 14:45, Chris Angelico a écrit :
Can you give an example? Let's say we have a simple blocking C function:
int get_data() {
sleep(2);
return 42;
}
I am not saying that I understand 100% and that this is the best way,
but it works for me:
% cat get_data.c
#include
On 2018-04-04, 07:27 GMT, Steven D'Aprano wrote:
> I'm no expert, but it seems to me that this has surely got to
> be crazy talk. Whatever task you're doing, processing it
> asynchronously doesn't reduce the amount of work. For example,
> if you want to download ten files, you still have to
On Wed, Apr 4, 2018 at 10:16 PM, Julien Salort wrote:
> In this case, the script spends most of its time waiting for a frame to be
> available on the cameras, and the time interval to query the other device.
> The fetching and processing of the frames take negligible time. The
Le 04/04/2018 à 09:27, Steven D'Aprano a écrit :
Yes, this exactly. And if you're writing a web app, or certain kinds of
desktop apps, these seems sensible. I don't want my browser to come to a
complete halt just because some resource is taking a few seconds to
respond.
But honestly, from
On Wed, Apr 4, 2018 at 9:02 PM, Richard Damon wrote:
> Asynchronous processing will use a bit more of some processing resources
> to handle the multi-processing, but it can be more efficient at fully
> using many of the resources that are available.
>
> Take your file
On Wed, Apr 4, 2018 at 8:42 PM, Paul Moore wrote:
> IMO,
> async has proved useful for handling certain types of IO bound
> workloads with lower overheads[1] than traditional multi-threaded or
> multi-process designs. Whether it's a good fit for any particular
> application
On 4/4/18 3:27 AM, Steven D'Aprano wrote:
> So, I'm, still trying to wrap my brain around async processing, and I
> started reading this tutorial:
>
> http://stackabuse.com/python-async-await-tutorial/
>
> and the very first paragraph broke my brain.
>
> "Asynchronous programming has been gaining
On Wed, Apr 4, 2018 at 5:27 PM, Steven D'Aprano
wrote:
> So, I'm, still trying to wrap my brain around async processing, and I
> started reading this tutorial:
>
> http://stackabuse.com/python-async-await-tutorial/
>
> and the very first paragraph broke my
On 4 April 2018 at 08:27, Steven D'Aprano
wrote:
> "Asynchronous programming has been gaining a lot of traction in the past
> few years, and for good reason. Although it can be more difficult than
> the traditional linear style, it is also much more
On 4 Apr 2018, at 9:27, Steven D'Aprano wrote:
Its as hard to wrap your brain around as parallel processing in
general,
but with even worse performance than sequential processing.
Am I totally wrong?
I would say that it all depends on what kind of stuff you're doing. I'm
no scheduling
I agree with you.
Async IO is more efficient than threading for **waiting** I/O.
When there are thousands of idle connections, async I/O is best idea.
On the other hand, async I/O uses more system calls for busy I/O.
For example, when building chat application which handles thousands
WebSocket
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